A domain-specific software architecture for adaptive intelligentsystems

A good software architecture facilitates application system development, promotes achievement of functional requirements, and supports system reconfiguration. We present a domain-specific software architecture (DSSA) that we have developed for a large application domain of adaptive intelligent systems (AISs). The DSSA provides: (a) an AIS reference architecture designed to meet the functional requirements shared by applications in this domain, (b) principles for decomposing expertise into highly reusable components, and (c) an application configuration method for selecting relevant components from a library and automatically configuring instances of those components in an instance of the architecture. The AIS reference architecture incorporates features of layered, pipe and filter, and blackboard style architectures. We describe three studies demonstrating the utility of our architecture in the subdomain of mobile office robots and identify software engineering principles embodied in the architecture     

A parallel architecture for distributed adaptive control

This paper describes the development of a flexible control system based on multiple T800 floating point transputers. In Part 1 of this paper, entitled 'The application of transputers to distributed control', an overview has been presented of distributed command and control systems (DCCS) and the suitability of the transputer for implementation within such systems discussed. In Part 2 of the article a transputer-based control module which has been developed at the University of Paisley is described. The module allows a number of different modes of operation in that it can be configured to act as either a fixed controller with the coefficients being down-loaded from a central control station, or as an adaptive controller which can make use of an explicit pole placement or linear quadratic Gaussian (LQG) structure. A supervisor, or coordination level, is incorporated into the adaptive controller to monitor the various parameters produced within the controller and direct the system to maintain a safe operation. This improves the applicability, robustness and integrity of the controller in real-time applications. The ease with which software tasks can be distributed over different transputer architectures allows the same software to be configured to accommodate between one and four transputers within the module. In this way the controller module can utilize a number of different transputer configurations depending on cost/performance trade-offs.The use of the transputer also allows the controller to communicate easily through its serial links with other controllers, hosts and external devices. In this way the module can be used as a universal controller node which can be easily incorporated into a large DCCS. Software has been developed to facilitate the production of this type of integrated environment such that a central network interface can initialize, analyse and supervise a number of the controller modules.     

面向服务的需求驱动自适应体系结构的研究

基于SOA构建了一种面向服务的需求驱动自适应体系结构(RDAA)来支持基于WebService的系统开发,RDAA充分考虑服务领域、机构管理与人的因素,吸取智能信息处理、语义Web以及软件工程的面向服务体系结构的研究、应用成果,具有适应环境与自我完善、自我发展能力.RDAA实现了与用户需求的直接对接,能够主动、自动识别用户需求模式而进行自适应调整,适用于需求复杂、远程协同、异构多样性的企业应用集成和资源整合管理.     

A hierarchical alternative updated adaptive Volterra filter with pipelined architecture

The pipelined adaptive Volterra filters (PAVFs) with a two-layer structure constitute a class of good low-complexity filters. They can efficiently reduce the computational complexity of the conventional adaptive Volterra filter. Their major drawbacks are low convergence rate and high steady-state error caused by the coupling effect between the two layers. In order to remove the coupling effect and improve the performance of PAVFs, we present a novel hierarchical pipelined adaptive Volterra filter (HPAVF)-based alternative update mechanism. The HPAVFs with hierarchical decoupled normalized least mean square (HDNLMS) algorithms are derived to adaptively update weights of its nonlinear and linear subsections. The computational complexity of HPAVF is also analyzed. Simulations of nonlinear system adaptive identification, nonlinear channel equalization, and speech prediction show that the proposed HPAVF with different independent weight vectors in nonlinear subsection has superior performance to conventional Volterra filters, diagonally truncated Volterra filters, and PAVFs in terms of initial convergence, steady-state error, and computational complexity.     

A set-theoretic model reference adaptive control architecture with dead-zone effect

A new set-theoretic model reference adaptive control architecture with dead-zone effect is presented. The key feature of our approach utilizes a new generalized restricted potential function, where it not only provides a user-defined uncertain dynamical system performance but also has the capability to stop the adaptation when system errors are small (i.e., inside dead-zone) — a practice adopted in adaptive control applications. The stability of the proposed technique is analyzed through showing the boundedness of an energy function in all possible variations and its experimental validation is also given through an aerospace testbed.     

Parallel architecture of adaptive MTD processors

A parallel systolic structure of the adaptive moving target detector (AMTD) is described. The adaptive signal processing is realized in the whole area of observation by a set of systolic processors operating in parallel. The cost of systolic AMTD implementation (necessary number of processing elements and computational steps) is also evaluated.     

The immersive effect of adaptive architecture

This paper explores the role of immersion in the generation of specific interactive effects, within the context of the emerging research field of Adaptive Architecture. Drawing on an existing biofeedback-driven prototype that links a person’s respiration to the form of their environment, the study presented here compared an immersive condition with a non-immersive condition to capture differences in participant experiences. The immersive condition afforded the majority of participants a relaxed, embodied experience, whereas the non-immersive condition left people unconnected. The study did not surface statistically significant differences in participants’ physiological responses between the two conditions. The study findings contribute to the understanding of our relationship with adaptive environments, underpinned by pervasive computing technologies, as they emerge in the Arts and Architecture.     

A variable structure gradient adaptive algorithm for a class of dynamical systems

A standard assumption in adaptive control is that the parameters being estimated are either constant or vary ‘slowly’ as a function of time. This paper investigates the adaptive control of a class of systems in which the parameters vary as a specified function of state. The dynamic structure of the systems may be either linear or nonlinear. For this class of systems, the state space is separated into distinct subsets. The parameters are then required to remain constant, or be slowly time varying, within the subsets. Given a controller for the system, an analysis of the output error dynamics and the parameter error dynamics leads to a parameter adaptation algorithm with a variable structure. The stability and convergence of both the parameter error and the output tracking error are investigated. An analysis of SISO linear systems with full state information is used to motivate and illustrate the treatment of SISO feedback linearizable systems.     

Neural adaptive regulation of unknown nonlinear dynamical systems

With this paper we extend our previous work on the subject, by including the case where the number of control inputs is different from the number of states which is frequently faced in control engineering problems. Uniform ultimate boundedness of the state and uniform boundedness of all other signals in the closed loop is guaranteed. Robustness of our algorithm due to the presence of a modeling error term which has linear growth with unknown growth coefficient is also established. Finally, the applicability of our control scheme is highlighted via simulation results.     

An architecture for adaptive multimedia content delivery

In this paper, we propose an architecture for multimedia content delivery considering Quality of Service (QoS), based on both the policy-based network and the best-effort network. The architecture consists of four fundamental elements: multimedia content model, application level QoS policy, QoS adaptation mechanism, and delivery mechanism. Applications based on current architecture loses their meaning by drastically degrading quality when network congestion occurs. Despite of this all-or-nothing architecture, applications based on our adaptive architecture can reduce its quality and then negotiate with the network entity, keeping its quality measure as much as possible even when network congestion occurs. We may consider a quality measure for Web pages, total page transmission time, and transmission order of inline objects as a segregation. We then define a language to specify application level QoS policies for Web pages and implement a delivery mechanism and a QoS adaptation mechanism to fulfill these policies. Kaname Harumoto, Ph.D.: He received the M.E. and Ph.D. (Eng.) degrees from Osaka University, Osaka, Japan, in 1994 and 1998, respectively. From 1994 through 1999, he was with the Department of Information Systems Engineering, Grauuate School of Engineering, Osaka University. Since November 1999, he has been an Assistant Professor in Computation Center (currently, the name has changed to Cybermedia Center), Osaka University. His research interests include database systems, especially in advanced network environments. He is a member of IEEE. Tadashi Nakano: He received the B.E. degree from Osaka University in 1999. Currently, he is a Ph.D. candidate in Graduate School of Engineering, Osaka University. His current reeearch interests include multimedia content delivery architecture. Shinji SHIMOJO, Ph.D.: He received the M.E. and a Dr.E. degrees from Osaka University in 1983 and 1986, respectively. From 1986 through 1989, he was an Assistant Professor in the Department of Information and Computer Sciences, Faculty of Engineering Science, Osaka University. From 1989 through 1998, he was an Associate Professor and since 1998, he has been a Professor in Computation Center (currently, the name has changed to Cybermedia Center), Osaka University. He was engaged in the project of object-oriented multimedia presentation system called Harmony. His current interests cover wide diversity of multimedia applications such as News On Demand System, multimedia database and networked virtual reality. He is a member of ACM and IEEE.     

动态自适应模块化神经网络结构设计

针对全连接前馈神经网络不能有效应对时变系统的问题, 提出一种动态自适应模块化神经网络结构. 该网络采用减法聚类算法在线辨识工况数据的空间分布, 利用RBF 神经元实现对数据样本空间的划分, 并结合模糊策略将不同子样本空间的数据动态分配给不同的子网络, 最后对各子网络的输出进行集成. 该模块化网络中子网络数量和子网络规模都能根据所学时变任务动态自适应调整. 通过对不同时变系统的预测表明了该网络能够有效跟踪时变系统.     

Pinning adaptive synchronization of a general complex dynamical network

There are two challenging fundamental questions in pinning control of complex networks: (i) How many nodes should a network with fixed network structure and coupling strength be pinned to reach network synchronization? (ii) How much coupling strength should a network with fixed network structure and pinning nodes be applied to realize network synchronization? To fix these two questions, we propose a general complex dynamical network model and then further investigate its pinning adaptive synchronization. Based on this model, we attain several novel adaptive synchronization criteria which indeed give the positive answers to these two questions. That is, we provide a simply approximate formula for estimating the detailed number of pinning nodes and the magnitude of the coupling strength for a given general complex dynamical network. Here, the coupling-configuration matrix and the inner-coupling matrix are not necessarily symmetric. Moreover, our pinning adaptive controllers are rather simple compared with some traditional controllers. A Barabási-Albert network example is finally given to show the effectiveness of the proposed synchronization criteria.     

Synchronization of uncertain complex dynamical networks via adaptive control

In this paper, synchronization of an uncertain dynamical network with time‐varying delay is investigated by means of adaptive control schemes. Time delays and uncertainties exist universally in real‐world complex networks. Especially, parameters of nodes in these complex networks are usually partially or completely uncertain. Considering the networks with unknown or partially known nodes, we design adaptive controllers for the corresponding complex dynamical networks, respectively. Several criteria guaranteeing synchronization of such systems are established by employing the Lyapunov stability theorem. Analytical and numerical results show that the proposed controllers have high robustness against parameter variations including network topologies, coupling structures, and strength. Copyright © 2008 John Wiley & Sons, Ltd.     

Neural network adaptive control for nonlinear nonnegative dynamical systems

Nonnegative and compartmental dynamical system models are derived from mass and energy balance considerations that involve dynamic states whose values are nonnegative. These models are widespread in engineering and life sciences and typically involve the exchange of nonnegative quantities between subsystems or compartments wherein each compartment is assumed to be kinetically homogeneous. In this paper, we develop a full-state feedback neural adaptive control framework for adaptive set-point regulation of nonlinear uncertain nonnegative and compartmental systems. The proposed framework is Lyapunov-based and guarantees ultimate boundedness of the error signals corresponding to the physical system states and the neural network weighting gains. In addition, the neural adaptive controller guarantees that the physical system states remain in the nonnegative orthant of the state-space for nonnegative initial conditions.     

An architecture framework for an adaptive extensible processor

To improve the performance of embedded processors, an effective technique is collapsing critical computation subgraphs as application-specific instruction set extensions and executing them on custom functional units. The problem with this approach is the immense cost and the long times required to design a new processor for each application. As a solution to this issue, we propose an adaptive extensible processor in which custom instructions (CIs) are generated and added after chip-fabrication. To support this feature, custom functional units are replaced by a reconfigurable matrix of functional units (FUs). A systematic quantitative approach is used for determining the appropriate structure of the reconfigurable functional unit (RFU). We also introduce an integrated framework for generating mappable CIs on the RFU. Using this architecture, performance is improved by up to 1.33, with an average improvement of 1.16, compared to a 4-issue in-order RISC processor. By partitioning the configuration memory, detecting similar/subset CIs and merging small CIs, the size of the configuration memory is reduced by 40%.     

动态自适应演进安全架构研究

自适应安全架构面对高级定向攻击具备智能与弹性安全防护能力,依托持续性地监测与回溯分析构建了自适应的未知攻击威胁预警体系,形成了集防御、监测、响应、预测为一体的安全防控流程闭环。基于自适应安全架构构建了适用于网络空间安全保密场景的动态防御体系,融合全息态势、智慧决策、动态防御等关键技术,提出了一种动态自适应演进的安全架构。     

AQuoSA—adaptive quality of service architecture

This paper presents an architecture for quality of service (QoS) control of time‐sensitive applications in multi‐programmed embedded systems. In such systems, tasks must receive appropriate timeliness guarantees from the operating system independently from one another; otherwise, the QoS experienced by the users may decrease. Moreover, fluctuations in time of the workloads make a static partitioning of the central processing unit (CPU) that is neither appropriate nor convenient, whereas an adaptive allocation based on an on‐line monitoring of the application behaviour leads to an optimum design. By combining a resource reservation scheduler and a feedback‐based mechanism, we allow applications to meet their QoS requirements with the minimum possible impact on CPU occupation. We implemented the framework in AQuoSA (Adaptive Quality of Service Architecture (AQuoSA). http://aquosa.sourceforge.net ), a software architecture that runs on top of the Linux kernel. We provide extensive experimental validation of our results and offer an evaluation of the introduced overhead, which is perfectly sustainable in the class of addressed applications. Copyright © 2008 John Wiley & Sons, Ltd.     

一种动态适应性软件体系结构模型理论研究

软件系统的演化需要具有灵活性、适应性的软件体系结构的支持。提出一种在组织结构上具有固有的动态性的软件体系结构理论模型——动态树型软件体系结构模型(DTSAM)。在DTSAM定义的软件体系结构组织结构下,软件系统的演化抽象成为一棵动态树的渐增和渐减。其中,所设计的渐增和渐减算法分别定义了动态树的增减过程;所设计的生长函数中适应性因子的调节,使得软件体系结构在组织结构层次上具有整体适应性和局部适应性。最后应用模型对例子系统仿真,其过程产生的结果也证实了这种适应性。